By Jim Germer
My wife Jeannine teaches elementary school. She’s 61, and she still shows kids how to write essays—not by prompting AI or “collaborating with AI,” but by building an argument from scratch. She teaches them to sit with a blank page until their own thinking emerges.
She’s in the minority now. And she knows it.
Most of her colleagues have quietly accepted that the future of education means teaching students how to use AI tools. How to prompt, check AI’s work, and “augment their thinking.” It all sounds reasonable, forward-looking, and no one really questions it anymore.
But Jeannine has seen what happens when kids skip the hard part, what happens when a child never has to sit with uncertainty long enough for an answer to appear. What she’s seeing isn’t “augmented thinking”—it’s more like mental atrophy.
What Formation Actually Looks Like
When a third-grader sits down to write a paragraph about their summer vacation, something important is supposed to happen. They’re supposed to sit there thinking, “I don’t know what to say yet.” They’re supposed to feel that awkwardness of a blank page, start with a clumsy sentence, realize it’s not great, and try again.
That friction, that cognitive discomfort, is not a bug in the learning process. It’s the entire point. Sitting with “I don’t know yet” is how the capacity to think gets built. The struggle is the training.
But when the student takes a photo of the assignment, AI generates three perfect sentences, and the student copies them onto the page, none of that happens. The output arrives. The assignment gets completed. The teacher—if they’re not paying close attention—sees neat handwriting and complete sentences and assumes the student is learning.
But the student isn’t learning. The student is completing.
And completion is not formation.
Jeannine can still tell the difference. She can read a sentence and immediately know whether a child wrote it or an AI did. Not because she’s running it through a detection tool, but because she knows what an eight-year-old voice sounds like. She knows the rhythm of a child’s thinking. She knows what authentic struggle produces.
That ability to hear the difference between formed thought and generated output is rarer than it sounds. And it is not being replaced.
What No One’s Talking About
The conversation about AI in education focuses almost entirely on students. What they’re losing. What they’re skipping. What the system should do to protect them.
But it’s not just students who are losing something. It’s teachers, too.
Among the new generation of teachers, the ones starting out now, many used AI throughout college—for essays, research papers, lesson plans, and teaching reflections. They graduated, got certified, and now they’re teaching kids.
Those teachers are used to writing with AI scaffolding.
Think about what this means for schools. A teacher who can’t write on their own can’t really teach writing. They can’t show students how to think through a problem or give real feedback on a student’s unique voice, because their own skills were shaped by AI. They don’t know what a real student voice sounds like, since they never fully developed their own.
This isn’t about blaming them. It’s just a fact about the environment they learned in, which didn’t give them what Jeannine’s training gave her.
What Pre-AI Teachers Still Have
Because of Florida’s Deferred Retirement Option Program, which lets experienced teachers keep working while putting off their pension, Jeannine will be in the classroom for several more years. Her students still have something that is becoming increasingly rare: a teacher who learned before AI and can show them what that means.
She can show what it means to struggle with thinking. She can model how to sit with uncertainty, revise a weak argument, and handle the discomfort of not knowing yet. She can show a child what it looks like to build a thought from nothing.
AI can’t do that. It just produces answers. It doesn’t show what it’s like to struggle or wait for an idea to come. Every response from AI is finished, smooth, and ready-made. An AI-dependent teacher can’t do it either. You can’t show students the process of independent thinking if you’ve never practiced it yourself.
The Pipeline Fracture
Think about how this builds over time. One teacher works with about 25 students a year. In thirty years, that’s 750 students. If a teacher can’t show independent thinking because they never learned it, none of those 750 students will see it in practice. And some of those students will go on to become teachers themselves.
The formation gap multiplies through the pipeline. Not through malice. Not through indifference. Through the simple structural fact that you cannot give what you do not have.
Within two generations, if things stay the same, most teachers will depend on AI. They won’t be able to write without help, grade without AI, or show independent thinking because they never learned it themselves. But everything will still look fine. Lessons will be taught, assignments finished, grades given, and students will graduate.
But the real goal of teaching—helping students learn how to think—will have quietly faded away.
This problem won’t show up on test scores or graduation rates. It only becomes obvious years later, when a bunch of grown-ups can’t do their jobs without constant help from AI, and no one can figure out why, because everything always looked fine on paper.
The Question the System Can’t Answer
When teachers like Jeannine are gone, who will show the next generation how to think for themselves?
Not AI. Not AI-dependent teachers. The question is structural, and under current incentives, the system has no clear answer.
Most schools try to turn this problem into an opportunity. They teach students how to use AI, how to write good prompts, how to get ready for a world full of AI. It sounds sensible, but it’s not really what’s needed.
To use AI well—to check its work, catch mistakes, or notice when it misses the point—you need skills that using AI too early can actually prevent you from building. I’m an accountant with forty years of experience. When I use AI to draft something, I can spot when it makes things too smooth, skips over something important, or just doesn’t get what I meant. I can do that because I have decades of experience to compare it to.
But a ten-year-old using AI to write a book report has nothing to compare it to. They can’t tell when AI missed the point, because they never read the book. They just accept whatever comes out, and each time they do, the foundation they should have been building slips a little further away.
Prompting is not thinking. Verifying AI output requires the judgment that AI use prevents from forming. You can’t teach responsible AI use to a student who never built the baseline to audit what AI produces.
What Retires with Jeannine
Colleges and universities spend a lot of time debating what AI means for testing, academic honesty, and the future of research papers. These are important questions. But there’s a more basic question that almost no one is asking: Who’s left in the room who can actually show a student what real thinking looks like?
Not just assign it, grade it, or use AI detection tools. The real need is to show it live, in front of a child, as a person working through something hard in real time.
Jeannine can do this. She does it every day. And when she leaves her classroom for the last time, something specific and irreplaceable will leave with her: the real-life example of how to build a thought from nothing, in a mind that had to do the work itself.
No credential system will record that loss. Test scores won’t show it. Graduation rates will stay steady. Everything will look the same on the surface. But a capacity that took decades to build—and that the current educational landscape no longer produces—will have left the room. And the system that should be asking how to keep it will mostly not notice it’s gone.
Jim Germer is a forensic CPA with nearly 40 years of professional experience examining institutional systems for the gaps between what’s claimed and what’s actually verifiable. He writes about AI’s effects on human cognition and formation at DigitalHumanism.ai and about AI governance and accountability at ThinkingSovereigtny.ai. His work on the “Formation Window”—the developmental period during which certain human capacities are built or lost—draws in part on decades of classroom observation from his wife, a longtime elementary school educator.
